Family-specific scaling laws in bacterial genomes

Among several quantitative invariants found in evolutionary genomics, one of the most striking is the scaling of the overall abundance of proteins, or protein domains, sharing a specific functional annotation across genomes of given size. The size of these functional categories change, on average, as power-laws in the total number of protein-coding genes. Here, we show that such regularities are not restricted to the overall behavior of high-level functional categories, but also exist systematically at the level of single evolutionary families of protein domains. Specifically, the number of proteins within each family follows family-specific scaling laws with genome size. Functionally similar sets of families tend to follow similar scaling laws, but this is not always the case. To understand this systematically, we provide a comprehensive classification of families based on their scaling properties. Additionally, we develop a quantitative score for the heterogeneity of the scaling of families belonging to a given category or predefined group. Under the common reasonable assumption that selection is driven solely or mainly by biological function, these findings point to fine-tuned and interdependent functional roles of specific protein domains, beyond our current functional annotations. This analysis provides a deeper view on the links between evolutionary expansion of protein families and the functional constraints shaping the gene repertoire of bacterial genomes.Comment: 41 pages, 16 figure

Translational Selection Is Ubiquitous in Prokaryotes

Codon usage bias in prokaryotic genomes is largely a consequence of background substitution patterns in DNA, but highly expressed genes may show a preference towards codons that enable more efficient and/or accurate translation. We introduce a novel approach based on supervised machine learning that detects effects of translational selection on genes, while controlling for local variation in nucleotide substitution patterns represented as sequence composition of intergenic DNA. A cornerstone of our method is a Random Forest classifier that outperformed previous distance measure-based approaches, such as the codon adaptation index, in the task of discerning the (highly expressed) ribosomal protein genes by their codon frequencies. Unlike previous reports, we show evidence that translational selection in prokaryotes is practically universal: in 460 of 461 examined microbial genomes, we find that a subset of genes shows a higher codon usage similarity to the ribosomal proteins than would be expected from the local sequence composition. These genes constitute a substantial part of the genome—between 5% and 33%, depending on genome size—while also exhibiting higher experimentally measured mRNA abundances and tending toward codons that match tRNA anticodons by canonical base pairing. Certain gene functional categories are generally enriched with, or depleted of codon-optimized genes, the trends of enrichment/depletion being conserved between Archaea and Bacteria. Prominent exceptions from these trends might indicate genes with alternative physiological roles; we speculate on specific examples related to detoxication of oxygen radicals and ammonia and to possible misannotations of asparaginyl–tRNA synthetases. Since the presence of codon optimizations on genes is a valid proxy for expression levels in fully sequenced genomes, we provide an example of an “adaptome” by highlighting gene functions with expression levels elevated specifically in thermophilic Bacteria and Archaea

Signatures of conformational stability and oxidation resistance in proteomes of pathogenic bacteria

Protein oxidation is known to compromise vital cellular functions. Therefore, invading pathogenic bacteria must resist damage inflicted by host defenses via reactive oxygen species. Using comparative genomics and experimental approaches, we provide multiple lines of evidence that proteins from pathogenic bacteria have acquired resistance to oxidative stress by an increased conformational stability. Representative pathogens exhibited higher survival upon HSP90 inhibition and a less-oxidation-prone proteome. A proteome signature of the 46 pathogenic bacteria encompasses 14 physicochemical features related to increasing protein conformational stability. By purifying ten representative proteins, we demonstrate in vitro that proteins with a pathogen-like signature are more resistant to oxidative stress as a consequence of their increased conformational stability. A compositional signature of the pathogens’ proteomes allowed the design of protein fragments more resilient to both unfolding and carbonylation, validating the relationship between conformational stability and oxidability with implications for synthetic biology and antimicrobial strategies

The Problem of Gene Patents

This Article submits that the main problem with gene patents is the failure to meet the condition of alternativeness of inventions-a condition that embodies a core function of the patent system. As a result, gene patents conflict with the very rationale of the patent system

The Origin and the Evolution of Firms

The firms and markets of today's complex socio-economic system developed in a spontaneous process termed evolution, in just the same way as the universe, the solar system, the Earth and all that lives upon it. Darwin's theory of evolution clearly demonstrated that evolution involved increasing organization. As we began to explore the molecular basis of life and its evolution, it became equally clear that it depended on the processing and communication of information. This book develops a consistent theory of evolution in its wider sense, examining the information based laws and forces that drive it. Exploring subjects as diverse as economics and the theories of thermodynamics, the author revisits the paradox of the apparent conflict between the laws of thermodynamics and evolution to arrive at a systems theory, tracing a continuous line of evolving information sets that connect the Big-Bang to the firms and markets of our current socio-economic system

Computational methods for tracking the evolution of complex bacterial communities

The focus of my PhD thesis was to study evolutionary aspects of host-associated microbial communities. In order to better understand these effects, I developed and applied computational methods to search for protein families that are under selection within metagenomes (Publication I) and applied them to various environments (see the articles “Structure and function of the bacterial root microbiota in wild and domesticated barley", and “Survival trade-offs in plant roots during colonization by closely related beneficial and pathogenic fungi”. One consistent finding of these studies was the high selective pressure acting on gene families associated with the bacterial defense system (the so-called CRISPR-Cas system) and families annotated as being related to bacteriophages. To study this CRISPR-phage relationship more closely, I systematically analysed CRISPR cassettes and CRISPR-related genes in samples from the Human Microbiome project (HMP) (Publication II). This resulted in one of the most comprehensive CRISPR collections to date. Further, we found novel sequence characteristics in the CRISPR loci and described the differences in the composition of CRISPR-associated genes in different body habitats and a potential relationship between the CRISPR defence system and the restriction modification system of bacteria. Furthermore, I performed a similar but less extensive search on metagenomic samples from infants: “Genomic variation and strain-specific functional adaptation in the human gut microbiome during early life”. Next, I turned my focus to study microbiome evolution in a gnotobiotic mouse model, since this provided the opportunity to study bacteria evolution on an intermediate scale of complexity. I contributed to the development of the mouse model described in the Manuscript “Genome-guided design of a defined mouse microbiota that confers colonization resistance against Salmonella enterica serovar Typhimurium” and a study comparing the stability of the community between animal facilities “Reproducible colonization of germ-free mice with the Oligo-Mouse-Microbiota in different animal facilities” and to a study focusing on the interaction network of this community. However, my main work with the OMM12 model has been to study community effects and evolution during repeated rounds of AB exposure (unpublished Publication III).Der Schwerpunkt meiner Doktorarbeit lag auf der Untersuchung evolutionärer Aspekte von wirtsassoziierten mikrobiellen Gemeinschaften. Um diese Effekte besser zu verstehen, habe ich computergestützte Methoden entwickelt und angewandt, um nach Proteinfamilien zu suchen, die in Metagenomen (Publikation I) der Selektion unterliegen, und sie auf verschiedene Umgebungen angewandt (siehe die Artikel “Structure and function of the bacterial root microbiota in wild and domesticated barley” und “Survival trade-offs in plant roots during colonization by closely related beneficial and pathogenic fungi”. Ein durchgängiges Ergebnis dieser Studien war der hohe Selektionsdruck, der auf Genfamilien wirkt, die mit dem bakteriellen Abwehrsystem (dem sogenannten CRISPR-Cas-System) und Familien, die als mit Bakteriophagen verwandt beschrieben werden, verbunden sind. Um diese CRISPR-Phagen-Beziehung genauer zu untersuchen, analysierte ich systematisch CRISPR-Kassetten und CRISPR-verwandte Gene in Proben aus dem Human Microbiome Project (HMP) (Publikation II). Dies führte zu einer der bisher umfassendsten CRISPR-Sammlungen. Darüber hinaus fanden wir neuartige Sequenzmerkmale in den CRISPR-Loci und beschrieben die Unterschiede in der Zusammensetzung von CRISPR-assoziierten Genen in verschiedenen Körperregionen sowie eine mögliche Beziehung zwischen dem CRISPR-Abwehrsystem und dem Restriktionsmodifikationssystem von Bakterien. Außerdem habe ich eine ähnliche, aber weniger umfangreiche Suche an metagenomischen Proben von Säuglingen durchgeführt: “Genomic variation and strain-specific functional adaptation in the human gut microbiome during early life”. Als Nächstes konzentrierte ich mich auf die Untersuchung der Mikrobiomevolution in einem gnotobiotischen Mausmodell, da dies die Möglichkeit bot, die Evolution von Bakterien auf einer mittleren Komplexitätsebene zu untersuchen. Ich war an der Entwicklung des Mausmodells beteiligt, das im Manuskript "Genom-guided design of a defined mouse microbiota that confers colonization resistance against Salmonella enterica serovar Typhimurium" und eine Studie zum Vergleich der Stabilität der OMM12 Gemeinschaft zwischen Tierhaltungsanlagen “Reproducible colonization of germ-free mice with the Oligo-Mouse-Microbiota in different animal facilities” sowie eine Studie, die sich auf das Interaktionsnetzwerk dieser Gemeinschaft konzentriert. Meine Hauptarbeit mit dem OMM12-Modell bestand jedoch darin, die Auswirkungen und die Entwicklung der Gemeinschaft während wiederholter AB-Expositionen zu untersuchen (unveröffentlichtes Manuscript III)

Genomic repertoires of DNA-binding transcription factors across the tree of life.

Sequence-specific transcription factors (TFs) are important to genetic regulation in all organisms because they recognize and directly bind to regulatory regions on DNA. Here, we survey and summarize the TF resources available. We outline the organisms for which TF annotation is provided, and discuss the criteria and methods used to annotate TFs by different databases. By using genomic TF repertoires from ∼700 genomes across the tree of life, covering Bacteria, Archaea and Eukaryota, we review TF abundance with respect to the number of genes, as well as their structural complexity in diverse lineages. While typical eukaryotic TFs are longer than the average eukaryotic proteins, the inverse is true for prokaryotes. Only in eukaryotes does the same family of DNA-binding domain (DBD) occur multiple times within one polypeptide chain. This potentially increases the length and diversity of DNA-recognition sequence by reusing DBDs from the same family. We examined the increase in TF abundance with the number of genes in genomes, using the largest set of prokaryotic and eukaryotic genomes to date. As pointed out before, prokaryotic TFs increase faster than linearly. We further observe a similar relationship in eukaryotic genomes with a slower increase in TFs

Measuring the Evolutionary Rewiring of Biological Networks

We have accumulated a large amount of biological network data and expect even more to come. Soon, we anticipate being able to compare many different biological networks as we commonly do for molecular sequences. It has long been believed that many of these networks change, or “rewire”, at different rates. It is therefore important to develop a framework to quantify the differences between networks in a unified fashion. We developed such a formalism based on analogy to simple models of sequence evolution, and used it to conduct a systematic study of network rewiring on all the currently available biological networks. We found that, similar to sequences, biological networks show a decreased rate of change at large time divergences, because of saturation in potential substitutions. However, different types of biological networks consistently rewire at different rates. Using comparative genomics and proteomics data, we found a consistent ordering of the rewiring rates: transcription regulatory, phosphorylation regulatory, genetic interaction, miRNA regulatory, protein interaction, and metabolic pathway network, from fast to slow. This ordering was found in all comparisons we did of matched networks between organisms. To gain further intuition on network rewiring, we compared our observed rewirings with those obtained from simulation. We also investigated how readily our formalism could be mapped to other network contexts; in particular, we showed how it could be applied to analyze changes in a range of “commonplace” networks such as family trees, co-authorships and linux-kernel function dependencies